Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/159844
Title: | Quantitative SARS-CoV-2 alpha variant B.1.1.7 tracking in wastewater by allele-specific RT-qPCR | Authors: | Lee, Wei Lin Imakaev, Maxim Armas, Federica McElroy, Kyle A. Gu, Xiaoqiong Duvallet, Claire Chandra, Franciscus Chen, Hongjie Leifels, Mats Mendola, Samuel Floyd-O'Sullivan, Róisín Powell, Morgan M. Wilson, Shane T. Berge, Karl L. J. Lim, Claire Y. J. Wu, Fuqing Xiao, Amy Moniz, Katya Ghaeli, Newsha Matus, Mariana Thompson, Janelle R. Alm, Eric J. |
Keywords: | Engineering::Environmental engineering | Issue Date: | 2021 | Source: | Lee, W. L., Imakaev, M., Armas, F., McElroy, K. A., Gu, X., Duvallet, C., Chandra, F., Chen, H., Leifels, M., Mendola, S., Floyd-O'Sullivan, R., Powell, M. M., Wilson, S. T., Berge, K. L. J., Lim, C. Y. J., Wu, F., Xiao, A., Moniz, K., Ghaeli, N., ...Alm, E. J. (2021). Quantitative SARS-CoV-2 alpha variant B.1.1.7 tracking in wastewater by allele-specific RT-qPCR. Environmental Science and Technology Letters, 8(8), 675-682. https://dx.doi.org/10.1021/acs.estlett.1c00375 | Project: | NRF2019-THE001-0003a | Journal: | Environmental Science and Technology Letters | Abstract: | The critical need for surveillance of SARS-CoV-2 variants of concern has prompted the development of methods that can track variants in wastewater. Here, we develop and present an open-source method based on allele-specific RT-qPCR (AS RT-qPCR) that detects and quantifies the B.1.1.7 variant, targeting spike protein mutations at three independent genomic loci that are highly predictive of B.1.1.7 (HV69/70del, Y144del, and A570D). Our assays can reliably detect and quantify low levels of B.1.1.7 with low cross-reactivity, and at variant proportions down to 1% in a background of mixed SARS-CoV-2. Applying our method to wastewater samples from the United States, we track the occurrence of B.1.1.7 over time in 19 communities. AS RT-qPCR results align with clinical trends, and summation of B.1.1.7 and wild-Type sequences quantified by our assays matches SARS-CoV-2 levels indicated by the U.S. CDC N1 and N2 assays. This work paves the way for AS RT-qPCR as a method for rapid inexpensive surveillance of SARS-CoV-2 variants in wastewater. | URI: | https://hdl.handle.net/10356/159844 | ISSN: | 2328-8930 | DOI: | 10.1021/acs.estlett.1c00375 | Schools: | Asian School of the Environment | Organisations: | Campus for Research Excellence and Technological Enterprise (CREATE) | Research Centres: | Singapore Centre for Environmental Life Sciences and Engineering (SCELSE) | Rights: | © 2021 The Authors. Published by American Chemical Society. This is an open-access article distributed under the terms of the Creative Commons Attribution License. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | ASE Journal Articles SCELSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR.pdf | 3.68 MB | Adobe PDF | ![]() View/Open |
SCOPUSTM
Citations
10
44
Updated on Jun 4, 2023
Web of ScienceTM
Citations
10
38
Updated on Jun 8, 2023
Page view(s)
61
Updated on Jun 8, 2023
Download(s) 50
50
Updated on Jun 8, 2023
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.